@article{JOIV15,
author = {Jacky Efendi and Muhammad Zul and Wawan Yunanto},
title = {Real Time Face Recognition using Eigenface and Viola-Jones Face Detector},
journal = {JOIV : International Journal on Informatics Visualization},
volume = {1},
number = {1},
year = {2017},
keywords = {Authentication; Face Recognition; EmguCV; Eigenface; Attendance; Viola-Jones},
abstract = {Authentication is the process of verifying one’s identity, and one of its implementation is in taking attendances in university’s lectures. Attendance taking is a very important matter to every academic institution as a way to examine students’ performance. Signature based attendance taking can be manipulated. Therefore it has problems in verifying the attendance validity. In this final project, a real time eigenface based face recognition is implemented in an application to do attendance taking. The input face image is captured using a webcam. The application itself is built in C#, utilizing EmguCV library. The application is developed using Visual Studio 2015. Face detection is done with Viola-Jones algorithm. The eigenface method is used to do facial recognition on the detected face image. In this final project, a total of 8 testings are done in different conditions. From the testings, it is found that this application can recognize face images with accuracy as high as 90% and as low as 6.67%. This solution can be used as an alternative for real-time attendance taking in an environment with 170 lux light intensity, webcam resolution of 320 x 240 pixel, and the subject standing 1 meter away while not wearing spectacles. The average recognition time is 0.18125 ms.},
issn = {2549-9904}, pages = {16--22}, doi = {10.30630/joiv.1.1.15},
url = {http://joiv.org/index.php/joiv/article/view/15}
}